IoT-D2D task allocation: an award-driven game theory approach

Abstract : An IoT-D2D cooperation framework for task allocation among objects in the IoT (Internet of Things) is presented. Proximity Services based on Device to Device (D2D) communication are used to enable direct interaction between IoT objects. The process is triggered by a node that decides to set up a cluster of nodes and then to coordinate the allocation strategy, where objects capable of performing the same tasks compete to get relevant remunerations. We then propose a game-theory based approach to find a solution maximizing objects utility functions. We prove that a Nash Equilibrium Point (NEP) can be found. Experimental results provide insights on the strategy performance
Keywords : Game theory IOT
Type de document :
Communication dans un congrès
ICT 2016 : 23rd International Conference on Telecommunications, May 2016, Thessaloniki, Greece. IEEE, Proceedings ICT 2016 : 23rd International Conference on Telecommunications, pp.1 - 6, 2016, 〈10.1109/ICT.2016.7500355〉
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https://hal.archives-ouvertes.fr/hal-01370189
Contributeur : Médiathèque Télécom Sudparis & Institut Mines-Télécom Business School <>
Soumis le : jeudi 22 septembre 2016 - 10:43:44
Dernière modification le : jeudi 11 janvier 2018 - 06:27:35

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Emad Mohamed Abd Elrahman Abousabea, Hossam Afifi, Luigi Aztori, Makhlouf Hadji, Virginia Pilloni. IoT-D2D task allocation: an award-driven game theory approach. ICT 2016 : 23rd International Conference on Telecommunications, May 2016, Thessaloniki, Greece. IEEE, Proceedings ICT 2016 : 23rd International Conference on Telecommunications, pp.1 - 6, 2016, 〈10.1109/ICT.2016.7500355〉. 〈hal-01370189〉

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